Existing methods identify only ≈10 Aδ-fibers in human sensory nerves per recording. This study examines methods to increase the detection of Aδ-fibers. Two to 20 averages of 500 replicate responses to epidermal nerve stimulation are obtained. Pairs of different averages are constructed. Each pair is analyzed with algorithms applied to amplitude and frequency to detect replication of responses to stimulation as “simultaneous similarities in two averages” (SS2AVs) at ≥99.5th percentile of control. In a pair of averages the latencies of amplitude and frequency SS2AVs for the same response to stimulation may differ by ≤0.25 ms. Therefore, Aδ-fibers are identified by the 0.25 ms moving sum of SS2AV latencies of the pairs of averages. Increasing averages increases pairs of different averages and detection of Aδ-fibers: from 2 to 10 Aδ-fibers with two averages (one pair) to >50 Aδ-fibers with 12–20 averages (66–190 pairs). Existing methods identify ≤10 Aδ-fibers in 10 averages/45 pairs with the medians of amplitude and frequency algorithms applied to all 45 pairs. This study identifies Aδ-fibers (i) by applying these algorithms at the 99.5th percentile of control, (ii) to each pair of averages and (iii) by the 0.25 ms sum of algorithm identified events (SS2AVs) in all pairs. These three changes significantly increase the detection of Aδ-fibers, e.g., in 10 averages/45pairs from 10 to 45. Three modifications of existing methods can increase the detection of Aδ-fibers to an amount suitable (>50 with ≥12 averages) for statistical comparison of different nerves.

中文翻译：

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多个平均记录来识别感觉神经中的 Aδ 纤维

现有方法每次记录只能识别人类感觉神经中的约 10 个 Aδ 纤维。本研究探讨了增加 Aδ 纤维检测的方法。获得对表皮神经刺激的 500 次重复反应的 2 至 20 个平均值。构造成对的不同平均值。使用应用于幅度和频率的算法对每对进行分析，以检测刺激反应的复制，作为控制≥99.5%的“两个平均值的同时相似性”（SS2AV）。在一对平均值中，对相同刺激的响应的幅度和频率 SS2AV 的延迟可能相差 ≤0.25 ms。因此，Aδ-纤维通过平均值对的 SS2AV 延迟的 0.25 ms 移动和来识别。增加平均值会增加不同平均值对和 Aδ 纤维的检测：从具有两个平均值的 2 到 10 个 Aδ 纤维（一对）到具有 12–20 个平均值的 > 50 个 Aδ 纤维（66–190 对）。现有方法可识别 10 个平均值/45 对中≤10 个 Aδ 纤维，并将振幅和频率算法的中值应用于所有 45 对。本研究通过 (i) 在控制的 99.5% 处应用这些算法来识别 Aδ 纤维，(ii) 应用于每对平均值，以及 (iii) 通过所有对中算法识别事件 (SS2AV) 的 0.25 毫秒总和。这三个变化显着增加了 Aδ 纤维的检测，例如，在 10 个平均值/45 对中从 10 增加到 45。对现有方法的三个修改可以将 Aδ 纤维的检测增加到适合的量（> 50，≥12 平均值）不同神经的统计比较。